Last month I described a new fully automated machine learning plugin to support simple blast-type email campaigns called Motion: Introducing Motion: A new (and better) way to do automated A/B testing

 

We've now got a beta version of the same machine intelligence capability for multistep campaigns. This addresses a long standing request for Oracle to support A/B testing on the canvas, but goes a good ways beyond that.

 

This deserves a post or two on its own but here's the problem with how A/B tests get done in Eloqua today: A/B/N tests send the same number of messages for each variation to learn what option is best. This means that as the number of message variations grows, you are sending more customers an inferior message during the testing period. In contrast, Motion experiments with any number of variations over time, incrementally learning which work best, and adapting to maximize overall campaign performance. Further, A/B sample populations frequently suffer from bias that make results of the test questionable - at best.

 

But this is a task that artificial intelligence - and specifically machine learning - can solve nicely.

 

Motion for the canvas works just like Motion for simple email campaigns, only you use the Motion Action Service instead of an Email Send step.  After you grant us permission to operate on your canvas, it looks like this:

Screen Shot 2016-10-25 at 07.35.33.png

 

It's just like any other valid cloud service, and very similar to the Email step - it's just that you're choosing multiple email assets to test over the population.  To be clear here: we are not futzing with the text of the email itself; we're simply using whatever you have stored in your Eloqua asset library. Motion allows you to test any number of variables: subject lines, text, layout, graphics - whatever you can store in your asset library.  Here's what that configuration looks like with three variations of, say, a subject line we'd like to test:

Screen Shot 2016-10-25 at 07.37.00.png

 

Once configured, the Motion step accepts contacts from e.g. a dynamic segment, and allows you to route contacts to subsequent steps - much as you'd do with an Email step. Like this:

Screen Shot 2016-10-25 at 07.47.20.png

 

In the above example, we actually have two totally separate optimizations running at two distinct drip-type steps.  You don't have to do this.  That second send step could just be a plain old single email send instead.  Just like for the simple email campaign, the way Motion works is to take in incremental audience responses (stored in the Activity DB) and improve subsequent send strategies day-by-day, learning which message treatments work better and shifting sends in favor of those winning treatments. With Motion, you're testing and optimizing over the entire population's preferences - not some small population carve-out. More signal + machine intelligence = better campaign and funnel performance.

 

You have access to the same elegant reports as Motion for simple campaigns.  We're constantly adding to these. See the previous post for a couple of examples.

 

Motion for canvas is in beta but ready for real use. The result is a measurably better way to do campaign message optimization that doesn't add work for you. Our intention with Motion is to begin to shift the way marketing is typically done - from undifferentiated generic blast to campaigns that listen, learn, and adapt to customers' preferences. This is only the first step.  Let me know if you'd like to join us on the journey; and see more at Motiva.